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Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation. Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural intensification, which are two key parameters in the Shared Socioeconomic Pathways (SSPs). Datasets mapping future land dynamics under different SSPs and climate change mitigation targets stem from different scenario assumptions, land data and modelling frameworks. This study aims to determine the role that these three factors play in the estimates of the evolution of cropland and pastureland in future SSPs under different climate scenarios from four main datasets largely used in the climate and land surface studies. The datasets largely agree with the representation of cropland at present-day conditions, but the identification of pastureland is ambiguous and shows large discrepancies due to the lack of a unique land-use category. Differences occur with future projections, even for the same SSP and climate target. Accounting for CO2 sequestration from revegetation of abandoned agricultural land and CO2 emissions from forest clearance due to agricultural expansion shows a net reduction in vegetation carbon stock for most SSPs considered, except SSP1. However, different datasets give differences in estimates, even when representative of the same scenario. With SSP1, the cumulative increase in carbon stock until 2050 is 3.3 GtC for one dataset, and more than double for another. Our study calls for a common classification system with improved detection of pastureland to harmonize projections and reduce variability of outcomes in environmental studies.

Abstract Droughts cause multiple ecological and social damages. Drought indices are key tools to quantify drought severity, but they are mainly limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (e.g., onset and cessation time) and help timely potential mitigation of adverse effects. Here, we propose a dataset of a daily drought index named daily evapotranspiration deficit index (DEDI), which is produced for global land areas from 1979 to 2022 using actual and potential evapotranspiration data. Validation efforts show that the DEDI dataset can well identify dry and wet variations in terms of spatial patterns and temporal evolutions when compared with other available drought indices on a daily scale. The dataset also has the capability to capture recent drying trends and to detect ecology- or agriculture-related droughts. Overall, the DEDI dataset is a step forward in facilitating drought monitoring and early warning at higher temporal resolution than other compared existing products.

Understanding ongoing vegetation dynamics is essential to disentangle ecosystem response to climate variability and identify threats and management opportunities. The basic distribution of vegetation cover and activity is largely determined by climatic conditions and management. Recent field studies suggest that herbivore-induced disturbances are important factors in vegetation dynamics, but analyses relying on long timeseries of empirical observations investigating the combined effect on vegetation of changing climate and herbivore densities are limited. In this study, the impact of temperature, precipitation, and large ungulates (both livestock and wildlife) on vegetation greenness (assessed with the enhanced vegetation index) from 2003 to 2021 in Norway are reconstructed for the growing season (May to October) and elucidated using multiple linear regression models. Vegetation greenness shows a widespread dominant increase in all months, with temperature being the dominant driver. Vegetation greenness is mostly affected by climate and ungulates in May, June and October (i.e., the start of growing season and the senescence), and at relatively high elevations (above 1000 m), where temperature is a limiting factor to vegetation growth. Precipitation can further contribute to explain the changes, especially in June and July. Generally, the positive temperature effect is amplified by increasing precipitation, but it has been hampered in places where precipitation was insufficient. Livestock mainly affect vegetation greenness negatively in northern grassland/shrubland ecosystems due to semi-domestic reindeer (Rangifer tarandus) grazing, while wild cervids (mostly moose Alces alces) negatively affect vegetation greenness in southeastern deciduous forests. The impact of livestock grazing on vegetation greenness is usually stronger than that of wildlife, which leads to a slightly more prevalent negative temperature-livestock interaction than temperature-wildlife interaction. Improving our understanding of these fundamental mechanisms is vital to support informed management of livestock, wildlife and natural vegetation under changing environmental conditions.

Abstract Negative emissions are essential to limit global warming, but their large‐scale deployment rises sustainability concerns. At the same time, agricultural soils are under increasing threat of degradation, as measured by losses in soil organic matter, water holding capacity, and nutrient retention, with increasing negative effects on plant productivity. Biochar from biomass residues is a technically mature option that does not compete for land and can typically restore key functions of degraded soils while delivering negative emissions. However, quantitative estimates of its potentials in Europe and a detailed spatially‐explicit analysis of the co‐benefits and trade‐offs for agricultural land are unclear. Here, we estimate an annual negative emission potential of biochar from forest and crop residues available in Europe from 1.7% to 3.9% of 2021s European greenhouse gas emissions (15.2%–35% of the agricultural emissions), depending on residue potentials and biochar scenarios. At the same time, biochar application to cropland increases water holding capacity (+6.5%‐9%), crop production (+7.1%‐8.4%), NH3 volatilization (+21.7%‐24.2%), and reduces soil N2O emissions (−13.7%–34.7%) and nitrogen leaching (−17.5%–22.7%). There are spatially heterogeneous trade‐offs for some soil effects (ammonia volatilization and yields) and air pollution (mainly due to emissions from biochar systems). Biochar offers synergistic solutions that co‐deliver across different sustainability challenges, but its optimal deployment requires strategies tailored to local conditions.

This study proposes a country-based life-cycle assessment (LCA) of several conversion pathways related to both on grid-connected Power-to-X (PtX) fuels and advanced biofuel production for maritime transport in Europe. We estimate the biomass resource availability (both agricultural and forest residues and second-generation energy crops from abandoned cropland), electricity mix, and a future-oriented prospective LCA to assess how future climate change mitigation policies influence the results. Our results indicate that the potential of PtX fuels to achieve well-to-wake greenhouse gas intensities lower than those of fossil fuels is limited to countries with a carbon intensity of the electricity mix below 100 gCO2eq kWh−1. The more ambitious FuelEU Maritime goal could be achieved with PtX only if connected to electricity sources below ca. 17 gCO2eq kWh−1 which can become possible for most of the national electricity mixes in Europe by 2050 if renewable energy sources will become deployed at large scales. For drop-in and hydrogen-based biofuels, biomass residues have a higher potential to reduce emissions than dedicated energy crops. In Europe, the potentials of energy supply from all renewable and low-carbon fuels (RLFs) range from 32 to 149% of the current annual fuel consumption in European maritime transport. The full deployment of RLFs with carbon capture and storage technologies could mitigate up to 184% of the current well-to-wake shipping emissions in Europe. Overall, our study highlights how the strategic use of both hydrogen-based biofuels and PtX fuels can contribute to the climate mitigation targets for present and future scenarios of European maritime transport.

Natural revegetation of abandoned cropland in biodiversity priority areas and afforestation and growth of bioenergy crop in other areas could achieve a climate change mitigation potential of 0.8–4.0 GtCO2-eq. per year, according to bottom-up estimates based on biomass yields and life-cycle emissions.

Using biomass from dedicated crops for energy production and natural vegetation regrowth are key elements in future climate change mitigation scenarios. However, there are still uncertainties about the mitigation potentials that can be achieved by the different land-based systems and how they perform relative to each other. In this study, we use harmonized future land use datasets to identify global land areas dedicated to second generation bioenergy crop production in 2050 under different climate scenarios. We then assess the global climate change mitigation potentials of using biomass for producing bioethanol with (BECCS) or without carbon capture and storage, biochar, or a synthetic fuel (e-methanol). For the latter, the electricity required to produce hydrogen for e-methanol synthesis is sourced from either wind power or the projected average electricity mix in 2050. Mitigation potential from natural regrowth on the identified land is also quantified. For all the cases, we modelled emissions of greenhouse gases from the life-cycle stages and use parameterized models to estimate local biomass growth rates. The identified land areas range from 1.95 to 13.8 million hectares and can provide from 30 to 178 mega ton (Mt) dry biomass annually from dedicated crops. Climate change mitigation potentials range from 11 to 257 MtCO2-eq. yr−1, depending on technological option and land availability. The largest mitigation is delivered by BECCS, but e-methanol can achieve similar findings when hydrogen is sourced from wind power. If hydrogen is produced from grid electricity, e-methanol can result in net positive emissions. E-methanol can also deliver more final energy than bioethanol (4.04 vs. 1.27 EJ yr−1). Natural vegetation regrowth can generally achieve higher mitigation than bioethanol, but less than biochar. An optimal combination of BECCS and natural vegetation regrowth can achieve a larger mitigation, up to 281 MtCO2-eq. yr−1, indicating that integrated solutions can help to achieve successful land management strategies for climate change mitigation.

Abstract The COVID-19 pandemic continues to pose substantial challenges to achieving the Sustainable Development Goals (SDGs). Exploring systematic SDG strategies is urgently needed to aid recovery from the pandemic and reinvigorate global SDG actions. Based on available data and comprehensive analysis of the literature, this paper highlights ongoing challenges facing the SDGs, identifies the effects of COVID-19 on SDG progress, and proposes a systematic framework for promoting the achievement of SDGs in the post-pandemic era. Progress towards attaining the SDGs was already lagging behind even before the onset of the COVID-19 pandemic. Inequitable distribution of food–energy–water resources and environmental crises clearly threaten SDG implementation. Evidently, there are gaps between the vision for SDG realization and actual capacity that constrain national efforts. The turbulent geopolitical environment, spatial inequities, and trade-offs limit the effectiveness of SDG implementation. The global public health crisis and socio-economic downturn under COVID-19 have further impeded progress toward attaining the SDGs. Not only has the pandemic delayed SDG advancement in general, but it has also amplified spatial imbalances in achieving progress, undermined connectivity, and accentuated anti-globalization sentiment under lockdowns and geopolitical conflicts. Nevertheless, positive developments in technology and improvement in environmental conditions have also occurred. In reflecting on the overall situation globally, it is recommended that post-pandemic SDG actions adopt a “Classification–Coordination–Collaboration” framework. Classification facilitates both identification of the current development status and the urgency of SDG achievement aligned with national conditions. Coordination promotes domestic/international and inter-departmental synergy for short-term recovery as well as long-term development. Cooperation is key to strengthening economic exchanges, promoting technological innovation, and building a global culture of sustainable development that is essential if the endeavor of achieving the SDGs is to be successful. Systematic actions are urgently needed to get the SDG process back on track.

Abstract The implementation of oxyfuel carbon capture and storage technologies in combination with use of alternative fuels comprising high biogenic shares is promoted as an attractive climate change mitigation option for the cement sector to achieve low or even negative carbon emissions. Here, we perform a prospective life cycle assessment of two state-of-the art cement plants, one in Sweden and one in Germany, under conventional and retrofitted oxyfuel conditions considering alternative fuel mixes with increasing bio-based fractions of forest residues or dedicated bioenergy crops. The analysis also considers effects of the projected changes in the electricity systems up to 2050. Retrofitting the cement plants to oxyfuel reduces climate change impacts between 74 and 91%, while with additional use of biomass as alternative fuel the cement plants reach negative emission between − 24 and − 169 gCO2eq. kgclinker −1, depending on operational condition, location, and biomass type. Additional emission reduction of − 10 (Sweden) and − 128 gCO2eq. kgclinker −1 (Germany) are expected from the decarbonization of the future electricity systems. Retrofitting the cement plants to oxyfuel conditions shows trade-offs with other environmental impacts (e.g., human toxicity, water and energy depletion), which are partially offset with projected changes in electricity systems. Our results illustrate the large climate change mitigation potential in the cement sector that can be achieved by the implementation of oxyfuel carbon capture and storage and biomass use as alternative fuel.

Understanding changes of ecosystem services and their influencing factors is crucial for more sustainable ecosystem management and conservation of nature contributions to people, especially in regions suffering high pressure from climate change and human activities, such as the Nordic countries. In this study, we assess multiple ecosystem services and their influencing factors in Denmark, Finland, Norway, and Sweden. We analyze changes in ecosystem services such as habitat quality, sediment retention, water yield, carbon sequestration, crop and roundwood production between 2003 and 2018. The relationships between ecosystem services and the main influencing factors (temperature, precipitation, elevation, population, livestock, and land use change) are assessed by means of the Spearman’s correlation coefficient and a new method that unravels synergies or tradeoffs at a grid level. Given the importance of forest management in the study region, an advanced land cover dataset that includes maps of forest harvest is produced and used as a basis for the analysis. Results show the large changes in ecosystem services during the study period and their spatial variations. Overall, the habitat quality is decreased, especially in the sites affected by forest management and agricultural production. Water yield and sediment retention increased due to higher precipitation (mainly in Norway). Higher temperature and forest management have generally increased carbon sequestration and provisioning services. The relationship between ecosystem services and their potential influencing factors differs across space. There are 10 out of 15 pairs of ecosystem services that predominantly show a tradeoff relationship, while the rest shows a synergy. In general, our results show the importance to monitor ecosystem services and understand the main drivers of their changes, so to design more sustainable resource management strategies that can secure a long-term delivery of ecosystem services.

The trade-offs and supply-demand relations of ecosystem services (ES) are at the frontier of geographical and ecological studies. However, previous studies have focused on either trade-offs or the supply-demand aspects, while ES conflicts and supply/demand contradictions have not been comprehensively examined. The relationship between ES trade-offs and supply-demand is logically valid and studying the coupling of both can provide approaches for simultaneously alleviating ES conflicts and supply-demand contradictions. This study, based on a review of previous analyses of ES trade-offs and supply-demand dynamics, proposes a new analytic framework to couple them. First, we define two types of trade-offs based on the directions of growth or decline of the two services. We also define the supply-demand balance area and the supply-demand risk area according to the ES flow characteristics. Second, the mechanisms driving ES trade-offs are clarified, and land-use scenarios are set based on the mechanisms. Third, the supply-demand spatial characteristics of ES are analyzed, and supply-demand risk areas are identified. Finally, scenario iterations are performed to minimize the supply-demand risk area at an acceptable trade-off intensity to identify an optimal land use plan, which simultaneously alleviates ES conflicts and supply-demand contradictions. This analytic framework offers new opportunities for improving sustainable ecosystem management.

Abstract Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of bioenergy, often used in conjunction with carbon capture and storage. We review the literature on bioenergy use for climate change mitigation, including studies that use top‐down integrated assessment models or bottom‐up modelling, and studies that do not rely on modelling. We summarize the state of knowledge concerning potential co‐benefits and adverse side effects of bioenergy systems and discuss limitations of modelling studies used to analyse consequences of bioenergy expansion. The implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and how bioenergy alters energy systems and land use. Depending on previous land use, widespread deployment of monoculture plantations may contribute to mitigation but can cause negative impacts across a range of other sustainability criteria. Strategic integration of new biomass supply systems into existing agriculture and forest landscapes may result in less mitigation but can contribute positively to other sustainability objectives. There is considerable variation in evaluations of how sustainability challenges evolve as the scale of bioenergy deployment increases, due to limitations of existing models, and uncertainty over the future context with respect to the many variables that influence alternative uses of biomass and land. Integrative policies, coordinated institutions and improved governance mechanisms to enhance co‐benefits and minimize adverse side effects can reduce the risks of large‐scale deployment of bioenergy. Further, conservation and efficiency measures for energy, land and biomass can support greater flexibility in achieving climate change mitigation and adaptation.

Mapping spatiotemporal land cover changes offers opportunities to better understand trends and drivers of environmental change and helps to identify more sustainable land management strategies. This study investigates the spatiotemporal patterns of changes in land covers, forest harvest areas and soil erosion rates in Nordic countries, namely Norway, Sweden, Finland, and Denmark. This region is highly sensitive to environmental changes, as it is experiencing high levels of human pressure and among the highest rates of global warming. An analysis that uses consistent land cover dataset to quantify and compares the recent spatiotemporal changes in land cover in the Nordic countries is missing. The recent products issued by the European Space Agency and the Copernicus Climate Change Service framework provide the possibility to investigate the historical land cover changes from 1992 to 2018 at 300 m resolution. These maps are then integrated with time series of forest harvest areas between 2004 and 2018 to study if and how forest management is represented in land cover products, and with soil erosion data to explore status and recent trends in agricultural land. Land cover changes typically involved from 4% to 9% of the total area in each country. Wetland showed the strongest reduction (11,003 km2, −11% of the wetland area in 1992), followed by forest (8,607 km2, −1%) and sparse vegetation (5,695 km2, −7%), while agriculture (15,884 km2, 16%) and settlement (3,582 km2, 84%) showed net increases. Wetland shrinkage dominated land cover changes in Norway (5,870 km2, −18%), followed by forest and grassland with a net gain of 3,441 km2 (3%) and 3, 435 km2 (10%), respectively. In Sweden, forest areas decreased 13,008 km2 (−4%), mainly due to agriculture expansion (9,211 km2, 29%). In Finland, agricultural areas increased by 5,982 km2 (24%), and wetland decreased by 6,698 km2 (−22%). Settlement had the largest net growth in Denmark (717 km2, 70%), mainly from conversion of agriculture land. Soil erosion rates in Nordic countries are lower than the global average, but they are exacerbating in several locations (especially western Norway). The integration of the land cover datasets with maps of forest harvest areas shows that the majority of the losses in forest cover due to forestry operations are largely undetected, but a non-negligible share of the forest-to-agriculture (up to 19%) or forest-to-grassland (up to 51%) transitions overlap with the harvested sites. Forestry activity in the study region primarily involves small-scale harvest events that are difficult to be detected at the 300 m resolution of the land cover dataset. An accurate representation of forest management remains a challenge for global datasets of land cover time series, and more interdisciplinary international efforts are needed to address this gap. Overall, this analysis provides a detailed overview of recent changes in land cover and forest management in Nordic countries as represented by state-of-the-art global datasets, and offers insights to future studies aiming to improve these data or apply them in land surface models, climate models, landscape ecology, or other applications.

Abstract The scientific literature contains contrasting findings about the climate effects of forest bioenergy, partly due to the wide diversity of bioenergy systems and associated contexts, but also due to differences in assessment methods. The climate effects of bioenergy must be accurately assessed to inform policy‐making, but the complexity of bioenergy systems and associated land, industry and energy systems raises challenges for assessment. We examine misconceptions about climate effects of forest bioenergy and discuss important considerations in assessing these effects and devising measures to incentivize sustainable bioenergy as a component of climate policy. The temporal and spatial system boundary and the reference (counterfactual) scenarios are key methodology choices that strongly influence results. Focussing on carbon balances of individual forest stands and comparing emissions at the point of combustion neglect system‐level interactions that influence the climate effects of forest bioenergy. We highlight the need for a systems approach, in assessing options and developing policy for forest bioenergy that: (1) considers the whole life cycle of bioenergy systems, including effects of the associated forest management and harvesting on landscape carbon balances; (2) identifies how forest bioenergy can best be deployed to support energy system transformation required to achieve climate goals; and (3) incentivizes those forest bioenergy systems that augment the mitigation value of the forest sector as a whole. Emphasis on short‐term emissions reduction targets can lead to decisions that make medium‐ to long‐term climate goals more difficult to achieve. The most important climate change mitigation measure is the transformation of energy, industry and transport systems so that fossil carbon remains underground. Narrow perspectives obscure the significant role that bioenergy can play by displacing fossil fuels now, and supporting energy system transition. Greater transparency and consistency is needed in greenhouse gas reporting and accounting related to bioenergy.

The COVID-19 pandemic has stalled and rolled back progress on Sustainable Development Goals (SDGs). Ecosystem services (ESs), defined as the contributions of ecosystems to human well-being, underpin the achievement of SDGs. To promote SDG achievement in post-pandemic era, we teased out the links between ESs and SDGs while examining the impact of COVID-19. We found that ESs benefited all SDGs, yet man-made pressures led to degradation of ecosystems and their services. There is broad consensus that the virus lurks in degraded ecosystems and generates spillover due to human interference. The pandemic and global lockdown/restriction disrupted the flow of ESs and altered human ESs demand, threatening the efforts for the SDGs. We suggested: 1) to study the association and traceability of ESs-SDGs under the pandemic; 2) to prioritize pressing issues such as health care, livelihood, and resource security and in the long run, we should promote human-nature harmony to achieve the SDGs; and 3) to enhance ESs and to promote the SDGs through local community efforts, ESs accounting, and ecosystem restoration. This paper provides insights into the importance of ESs to the SDGs and the ways to integrate ESs into socio-economic development to promote the SDG achievement after the pandemic.

The implementation of strategies to achieve the Sustainable Development Goals (SDGs) is frequently hindered by potential trade-offs between priorities for either environmental protection or human well-being. However, ecosystem services (ES)-based solutions can offer possible co-benefits for SDGs implementation that are often overlooked or underexploited. In this study, we cover this gap and investigate how experts from different countries value the SDGs and relate them with ES. A total of 66 countries participated to the survey, and answers were grouped into three macro-regions: Asia; Europe, North America, and Oceania (ENO); Latin America, Caribbean and Africa (LA). Results show that the most prioritized SDGs in the three macro-regions are usually those related to essential material needs and environmental conditions, such as SDG2 (Zero Hunger), SDG1 (No Poverty), and SDG6 (Clean Water). At a global scale, the number of prioritized synergies between SDGs and ES largely exceeded trade-offs. The highest amount of synergies was observed for SDG1 (No Poverty), mainly with SDG2, SDG3 (Good Health), SDG5 (Gender Equality), and SDG8 (Economic Growth). Other major synergies among SDGs include SDG14-15 (Life below water - Life on land), SDG5-10 (Gender Equity - Reduced Inequality), and SDG1-2 (No poverty - Zero Hunger). At a global scale, SDG15, SDG13, SDG14, and SDG6 were closely related to ES like climate regulation, freshwater, food, water purification, biodiversity, and education. SDG11 (Sustainable Cities) and SDG3 were also relevant in Asia and in LA, respectively. Overall, this study shows the potential to couple future policies that can implement SDGs' strategies while adopting ES-based solutions in different regions of the world.

Protected areas (PAs) are the critical societal tool to preserve biodiversity and ecosystem services (ESs), but human disturbances frequently threaten them. Here, we used multiple data sources to map the human footprint as a proxy for identifying the intensity of human activities on the Qinghai-Tibet Plateau and therein nature reserves (NRs, the primary category of PAs in China). We found that the human footprint on the Qinghai-Tibet Plateau has increased by 22% since 2000, and on average, human pressure inside NRs was 60% lower than outside. However, human pressure was identified in the majority of the NRs, with only 30% of protected land free from any measurable pressure. From a total of 53 NRs, 28 showed over 10% increase in human footprint, and 6 NRs had over 70% of their extent under intense human pressure (human footprint score≥4). Furthermore, a higher proportion of ESs in NRs is subjected to high levels of human pressure and are therefore at risk, particularly soil and water retention. The applied regression model revealed that large NRs are more resilient to human pressure than NRs with the longer establishment. The continuous human footprint increase may hinder the current and future ESs supply. Our analysis shows evidence-based results to promote the mitigation of human pressures in PAs.

Land cover change contributes to regional climate trends. Here, the authors use high-resolution land cover maps and state-of-the-art climate modelling to assess land cover change effects across Europe over 1992-2015, showing widespread cooling after agricultural abandonment but also different, region-specific effects.

Ecosystem authenticity is a concept for understanding the status of an ecosystem and provides useful information for making environmental management plans. However, approaches for quantitative ecosystem authenticity evaluation over large area are still rare. In this study, a conceptual framework of “Pattern-Process-Function-Resilience” is proposed to quantitatively evaluate regional ecosystem authenticity. Firstly, a composite index is calculated to estimate the self-adjustment ability and the level of biodiversity of the ecosystem. Then, the ratio between the composite indices are computed at the final and initial periods, and used to determine whether the ecosystem authenticity is protected or damaged, as well as the degrees to which the authenticity is protected or damaged by categorizing the ratio into five levels. A case study was conducted to quantify and evaluate the ecosystem authenticity over the Qinghai-Tibet Plateau (QTP) and the alternative locations of its twenty national parks from 2000 to 2015. Results show that regions with protected or damaged ecosystem authenticity cover about 95% and 5% of the entire QTP, respectively. Five of the twenty national parks alternative locations have damaged ecosystem authenticity. Areas with damaged authenticity are mainly distributed over the southeastern QTP, which suffered from deforestation and increased frequency of mountain hazards, including debris flow, flash flood, landslide, collapse, and snow avalanche. The approach presented in this study is instrumental to support future case-specific management and restoration strategies.

Agroforestry is a land management practice where trees are grown around or among crops or pastureland. This integration of agriculture and forestry is frequently seen as an option that can secure food security and co-deliver a range of environmental benefits. However, quantitative studies simultaneously integrating multiple aspects of agroforestry are rare. Focusing on four sustainability goals, namely adaptation to climate change, biodiversity conservation, climate change mitigation and rural development, this study investigated co-benefits and adverse side-effects of shaded agroforests above cocoa, coffee, oil palm, banana and citrus plantations in tropical humid West Africa. Time series of remote sensing land cover datasets were used to quantify and map recent land cover transitions in the region, and a field study in 25 agroforestry plots in Togo provided biomass carbon measurements in over 3000 trees, in addition to local farmers interviews. Estimates of theoretical agroforestry expansion and associated carbon sequestration potential in the region were compared to regional emissions from fossil fuels and deforestation. We found that about 1.6 Mha of losses in evergreen forests occurred between 1992 and 2015 (corresponding to 17% of the forest area originally present in 1992), while agricultural areas increased by 2.4 Mha (+5% relative to 1992). On average, trees in the studied agroforestry plots store 83.7 ± 7.0 t C/ha. We found synergies between rural development and adaptation benefits, no clear relationship between biodiversity and carbon storage, and a trade-off between high carbon stocks and crop yields. This trade-off can be minimized with an optimal management of agroforestry by using a mix of tree species that store medium carbon stocks and can enhance yields, soil fertility and climate resilience. In general, plant functional diversity, i.e. a balanced mix of shade trees, fruit trees, palms and bananas, emerged as a key feature of successful agroforestry systems. Besides, agroforestry trees co-products are reported as an additional, diversified source of income for local farmers. A large-scale deployment of agroforestry over seven countries in West Africa can sequester up to 135 Mt CO2/year over two decades, corresponding to about 166% of the carbon emissions from fossil fuels and deforestation in the region. Overall, agroforestry practices in tropical humid West Africa offer multiple-win solutions that are relevant to address major local and global environmental challenges. Increasing cooperation among local farmer communities, national authorities, and international organizations are instrumental to overcome the barriers for a future expansion of agroforestry systems in the region.

A ramp-up of bioenergy supply is vital in most climate change mitigation scenarios. Using abandoned land to produce perennial grasses is a promising option for near-term bioenergy deployment with minimal trade-offs to food production and the environment. The former Soviet Union (fSU) experienced substantial agricultural abandonment following its dissolution, but bioenergy potentials on these areas and their water requirements are still unclear. We integrate a regional land cover dataset tailored towards cropland abandonment, an agro-ecological crop yield model, and a dataset of sustainable agricultural irrigation expansion potentials to quantify bioenergy potentials and water requirements on abandoned land in the fSU. Rain-fed bioenergy potentials are 3.5 EJ yr ^−1 from 25 Mha of abandoned land, with land-sparing measures for nature conservation. Irrigation can be sustainably deployed on 7–18 Mha of abandoned land depending on water reservoir size, thereby increasing bioenergy potentials with rain-fed production elsewhere to 5.2–7.1 EJ yr ^−1 . This requires recultivating 29–33 Mha combined with 30–63 billion m ^3 yr ^−1 of blue water withdrawals. Rain-fed productive abandoned land equals 26%–61% of the projected regional fSU land use for dedicated bioenergy crops in 2050 for 2 °C future scenarios. Sustainable irrigation can bring productive areas up to 30%–80% of the projected fSU land requirements. Unraveling the complex interactions between land availability for bioenergy and water use at local levels is instrumental to ensure a sustainable bioenergy deployment.

Abstract The importance to consider changes in surface albedo and go beyond simple carbon accounting when assessing climate change impacts of forestry and land use activities is increasingly recognized. However, representation of albedo changes in climate models is complex and highly parameterized, thereby limiting their applications in climate impact studies. The availability of simple yet reliable albedo models can enhance consideration of albedo changes in land use studies. We propose a set of simplified models for estimating surface albedo in a boreal forest. We process and harmonize datasets of remotely‐sensed albedo estimates, forest structure parameters, and meteorological records for different forest locations in Norway. By combining linear unmixing with nonlinear programming, we simultaneously produce albedo estimates at the same resolution of the land cover dataset (16 m, notably higher than satellite retrievals) and a variety of flexible models for albedo predictions. We test different combinations of functional forms, variables, and constraints, including variants specific for snow‐free conditions. We find that models capture the seasonal pattern of surface albedo and the interactive effect of forest structures and meteorological parameters, and many of them show good statistical scores. The cross‐validation exercise shows that the models derived from one area perform reasonably well when applied to other forested areas in Norway, regardless of the temporal and spatial scales. By incorporating changes in forest structure and climate conditions as explicit variables, these models are simple to be used in different applications aiming at estimating albedo changes from forest management and climate change.

Abstract Background Forests and forest products can significantly contribute to climate change mitigation by stabilizing and even potentially decreasing the concentration of carbon dioxide (CO2) in the atmosphere. Harvested wood products (HWP) represent a common widespread and cost-efficient opportunity for negative emissions. After harvest, a significant fraction of the wood remains stored in HWPs for a period that can vary from some months to many decades, whereas atmospheric carbon (C) is immediately sequestered by vegetation re-growth. This temporal mismatch between oxidation of HWPs and C uptake by vegetation generates a net sink that lasts over time. The role of temporary carbon storage in forest products has been analysed and debated in the scientific literature, but detailed bottom-up studies mapping the fate of harvested materials and quantifying the associated emission profiles at national scales are rare. In this work, we quantify the net CO2 emissions and the temporary carbon storage in forest products in Norway, Sweden and Finland for the period 1960–2015, and investigate their correlation. We use a Chi square probability distribution to model the oxidation rate of C over time in HWPs, taking into consideration specific half-lives of each category of products. We model the forest regrowth and estimate the time-distributed C removal. We also integrate the specific HWP flows with an emission inventory database to quantify the associated life-cycle emissions of fossil CO2, CH4 and N2O. Results We find that assuming an instantaneous oxidation of HWPs would overestimate emissions of about 1.18 billion t CO2 (cumulative values for the three countries over the period 1960–2015).We also find that about 40 years after 1960, the starting year of our analysis, are sufficient to detect signs of negative emissions. The total amount of net CO2 emissions achieved in 2015 are about − 3.8 million t CO2, − 27.9 t CO2 and − 43.6 t CO2 in Norway, Sweden, and Finland, respectively. Conclusion We argue for a more explicit accounting of the actual emission rates from HWPs in carbon balance studies and climate impact analysis of forestry systems and products, and a more transparent inclusion of the potential of HWP as negative emissions in perspective studies and scenarios. Simply assuming that all harvested carbon is instantaneously oxidized can lead to large biases and ultimately overlook the benefits of negative emissions of HWPs.

A general issue in climate science is the handling of big data and running complex and computationally heavy simulations. In this paper, we explore the potential of using machine learning (ML) to spare computational time and optimize data usage. The paper analyzes the effects of changes in land cover (LC), such as deforestation or urbanization, on local climate. Along with green house gas emission, LC changes are known to be important causes of climate change. ML methods were trained to learn the relation between LC changes and temperature changes. The results showed that random forest (RF) outperformed other ML methods, and especially linear regression models representing current practice in the literature. Explainable artificial intelligence (XAI) was further used to interpret the RF method and analyze the impact of different LC changes on temperature. The results mainly agree with the climate science literature, but also reveal new and interesting findings, demonstrating that ML methods in combination with XAI can be useful in analyzing the climate effects of LC changes. All parts of the analysis pipeline are explained including data pre-processing, feature extraction, ML training, performance evaluation, and XAI.

Many future scenarios expect a key role for the land use sector to stabilize temperature rise to 2 °C or less. Changes in land cover can influence the climate system, and the extent and magnitude of the anthropogenic modifications at local and regional scales is still largely unexplored. In this study, we use the regional climate model COSMO-CLM v.4.8 to quantify the climate response to idealized extreme land cover changes in Europe. We simulate four idealized land use transitions involving abrupt conversion of today forestland to bare land or herbaceous vegetation, and conversion of today cropland to evergreen needle-leaf forest or deciduous broad-leaf forest. We find that deforestation to bare land and herbaceous vegetation causes an annual mean regional cooling of −0.06 ± 0.09 (mean ± standard deviation) and −0.13 ± 0.08, respectively. Afforestation to needle-leaf and broad-leaf forests leads to a mean warming of 0.15 ± 0.09 °C and 0.13 ± 0.09 °C, respectively. Precipitation declines after forest clearance and increases with afforestation, but the spatial variability is high. Temperature impacts are usually more significant in the grid cells affected by land cover change and show a clear latitudinal pattern and seasonal variability. The mean temperature response to deforestation turns from positive to negative between 50 and 55° latitude, and shows the strongest cooling in spring (>2 °C, high latitudes) but warming in summer (>1 °C), when the average number of hot days is increased. Afforestation has the major average warming impacts in winter, where the frequency of cold temperature extremes is reduced. Overall, biophysical effects from land cover changes shape European climate in different ways, and further developments can ultimately assist decision makers to modulate land management strategies at different scales in light of climate change mitigation and adaptation.

Environmental impact studies of forest bioenergy systems usually account for CO _2 emissions and removals and identify the so-called carbon debt of bioenergy through comparison with a reference system. This approach is based on a simple sum of fluxes and does not consider any direct physical impact or climate system response. Other recent applications go one step further and elaborate impulse response functions (IRFs) and subsequent metrics for biogenic CO _2 emissions that are compatible with the life-cycle assessment (LCA) methodology. However, a thorough discussion about the role of the different metrics in the interpretation of the climate impacts of forest bioenergy systems is still missing. In this work, we assess a single LCA dataset of selected bioenergy systems using different emission metrics based on cumulative CO _2 emissions, radiative forcing and global surface temperature. We consider both absolute and normalized metrics for single pulses and sustained emissions. The key challenges are the choice of end point (emissions, concentration, radiative forcing, change in temperature, etc), the type of measure (instantaneous or time-integrated) and the treatment of time. Bioenergy systems usually perform better than fossil counterparts if assessed with instantaneous metrics, including global surface temperature change, and in some cases can give a net global cooling effect in the short term. The analysis of sustained, or continuous emissions, also shows that impacts from bioenergy systems are generally reversible, while those from fossil fuels are permanent. As shown in this study, the metric choice can have a large influence on the results. The dominant role traditionally assigned to cumulative metrics in LCA studies and climate impact accounting schemes should therefore be reconsidered, because such metrics can fail to capture important time dependences unique to the biomass system under analysis (to which instantaneous metrics are well suited).

Production of biomass for bioenergy can alter biogeochemical and biogeophysical mechanisms, thus affecting local and global climate. Recent scientific developments have mainly embraced impacts from land use changes resulting from area-expanded biomass production, with several extensive insights available. Comparably less attention, however, has been given to the assessment of direct land surface–atmosphere climate impacts of bioenergy systems under rotation such as in plantations and forested ecosystems, whereby land use disturbances are only temporary. Here, following IPCC climate metrics, we assess bioenergy systems in light of two important dynamic land use climate factors, namely, the perturbation in atmospheric carbon dioxide (CO _2 ) concentration caused by the timing of biogenic CO _2 fluxes, and temporary perturbations to surface reflectivity (albedo). Existing radiative forcing-based metrics can be adapted to include such dynamic mechanisms, but high spatial and temporal modeling resolution is required. Results show the importance of specifically addressing the climate forcings from biogenic CO _2 fluxes and changes in albedo, especially when biomass is sourced from forested areas affected by seasonal snow cover. The climate performance of bioenergy systems is highly dependent on biomass species, local climate variables, time horizons, and the climate metric considered. Bioenergy climate impact studies and accounting mechanisms should rapidly adapt to cover both biogeochemical and biogeophysical impacts, so that policy makers can rely on scientifically robust analyses and promote the most effective global climate mitigation options.